{"meta":{"query_hash":"bdb4e5186fa7","filters":{"venue":"Bulletin of Health Services Research"},"cohort_total":3,"direct_labels_cover":0,"predictions_cover":3,"exported":3,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/bdb4e5186fa7","api":"https://metacan.xera.ac/api/v1/cohort?venue=Bulletin+of+Health+Services+Research"},"results":[{"id":"W7154837391","doi":"10.71465/bhsr50","title":"Leveraging Telemedicine and Health Data Analytics to Improve Patient Safety and Service Delivery in Low-Resource Healthcare Systems","year":2024,"lang":"","type":"article","venue":"Bulletin of Health Services Research","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Digital health; Telemedicine; Analytics; Health care; Multidisciplinary approach; Big data; Resilience (materials science); Patient safety","score_opus":0.10377575726881191,"score_gpt":0.42592437269587924,"score_spread":0.3221486154270673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154837391","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14989527,0.36120507,0.12335836,0.22099048,0.0026780013,0.0007797,0.0010439038,0.00060344767,0.1394457],"genre_scores_gemma":[0.72163755,0.22004582,0.043879077,0.008936735,0.0019036235,0.00028430205,0.00043187023,0.000058291414,0.0028227272],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99617934,0.0023675268,0.00030395846,0.00022181313,0.00065120804,0.00027610618],"domain_scores_gemma":[0.98738945,0.009549065,0.0009645495,0.0005079095,0.001132272,0.0004567379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067756725,0.0003134843,0.00028884097,0.0023300836,0.00055528485,0.0040414985,0.0008983322,0.0010943037,0.00239735],"category_scores_gemma":[0.015877502,0.00018631012,0.00061305804,0.0023586405,0.0013198225,0.004665639,0.0030781352,0.001559014,0.0003691252],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010802101,0.0002547036,0.021540653,0.008576774,0.00031940025,0.00056326174,0.0031851328,0.003318546,0.0027285537,0.07969606,0.014118604,0.8655902],"study_design_scores_gemma":[0.00014310055,0.0011207316,0.050028868,0.02987879,0.0007196976,0.0019269991,0.01700953,0.013782905,0.011050339,0.14707561,0.72707725,0.00018621341],"about_ca_topic_score_codex":0.002030419,"about_ca_topic_score_gemma":0.0023037032,"teacher_disagreement_score":0.0067756725,"about_ca_system_score_codex":0.0015615313,"about_ca_system_score_gemma":0.0052584847,"threshold_uncertainty_score":0.035833657},"labels":[],"label_agreement":null},{"id":"W7154838436","doi":"10.71465/bhsr45","title":"THE ROLE OF ARTIFICIAL INTELLIGENCE IN EARLY DISEASE DETECTION","year":2024,"lang":"","type":"article","venue":"Bulletin of Health Services Research","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Disease; Realm; Applications of artificial intelligence; Process (computing); Health care; Infectious disease (medical specialty); Patient care","score_opus":0.1230230567456314,"score_gpt":0.4772523148677041,"score_spread":0.3542292581220727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154838436","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045222953,0.15437786,0.5444647,0.16113,0.002985132,0.00041977718,0.0010929493,0.0014071977,0.08889938],"genre_scores_gemma":[0.59298915,0.08682868,0.29687104,0.012553585,0.0035653303,0.00025364704,0.0007842246,0.00017454449,0.0059798597],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99220216,0.0047155647,0.00043162963,0.00073418295,0.0017202058,0.00019622437],"domain_scores_gemma":[0.9639821,0.030474886,0.0014647802,0.0016897721,0.0018796261,0.0005087325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010029285,0.0008498524,0.0008275242,0.00394144,0.0008636486,0.005364156,0.001497918,0.0020054595,0.0020260012],"category_scores_gemma":[0.03332982,0.00038203233,0.0006462769,0.0023591588,0.004022965,0.0047509815,0.0020399117,0.003321231,0.00082807406],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001965423,0.0003357173,0.036902204,0.002030144,0.00035685158,0.00072466966,0.0013723344,0.019806989,0.002960567,0.18625364,0.028300965,0.7207594],"study_design_scores_gemma":[0.000060942606,0.00037194628,0.017248774,0.0027495876,0.00025824877,0.0020386565,0.0016417473,0.08512523,0.0033702182,0.740181,0.14673594,0.00021773473],"about_ca_topic_score_codex":0.0031101715,"about_ca_topic_score_gemma":0.002459833,"teacher_disagreement_score":0.010029285,"about_ca_system_score_codex":0.0014505134,"about_ca_system_score_gemma":0.0026004692,"threshold_uncertainty_score":0.053040564},"labels":[],"label_agreement":null},{"id":"W7154850841","doi":"10.71465/bhsr51","title":"The Role of Hospital Administration in Improving Patient-Centered Care Delivery","year":2025,"lang":"","type":"article","venue":"Bulletin of Health Services Research","topic":"Patient Satisfaction in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Health care; Healthcare delivery; Administration (probate law); Quality management; Quality (philosophy); Health care delivery; Health administration; Organizational culture","score_opus":0.040665555776416666,"score_gpt":0.42075879777424796,"score_spread":0.3800932419978313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154850841","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20072278,0.03794046,0.056367256,0.47299308,0.0032564711,0.00062345323,0.00021320675,0.00069501036,0.22718832],"genre_scores_gemma":[0.9506758,0.010634925,0.015335111,0.016170852,0.0012755977,0.00016025212,0.00005774955,0.00007622134,0.0056135776],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.96677464,0.02637172,0.0009423918,0.00050884666,0.0035093313,0.0018930485],"domain_scores_gemma":[0.9482523,0.022155514,0.006718535,0.0018855027,0.008861238,0.012126895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023825433,0.0003058982,0.00035147998,0.0010085333,0.0032162885,0.009470309,0.0007184565,0.0010594407,0.004402217],"category_scores_gemma":[0.024978641,0.0002132823,0.00028423624,0.0012807028,0.0029085681,0.0032147206,0.0036300682,0.0027871442,0.00090097147],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017343232,0.00085015653,0.07453965,0.0015075543,0.00015829701,0.0003452148,0.016123554,0.0014065815,0.0020132486,0.14234899,0.07665222,0.6838811],"study_design_scores_gemma":[0.00013679138,0.002118923,0.12443913,0.0036419115,0.00016235288,0.0010651592,0.034309264,0.0033661462,0.0037428492,0.070155144,0.7566575,0.00020490978],"about_ca_topic_score_codex":0.002948807,"about_ca_topic_score_gemma":0.0026762064,"teacher_disagreement_score":0.023825433,"about_ca_system_score_codex":0.0045311884,"about_ca_system_score_gemma":0.02241206,"threshold_uncertainty_score":0.12600243},"labels":[],"label_agreement":null}]}